This study aimed to identify indicator species and explore the most important environmental and management variables contributing to vegetation distribution in a hilly upper dam landscape in Zagros Mountain chain, Ira...This study aimed to identify indicator species and explore the most important environmental and management variables contributing to vegetation distribution in a hilly upper dam landscape in Zagros Mountain chain, Iran. A stratified random sampling method was used to collect topographic, edaphic, management and vegetation data. The density and cover percentage of perennial species were measured quantitatively. Indicator species were identified using the two-way indicator species analysis. Besides calculating physiognomic factors in sample sites, 24 soil samples were collected from 0 to 30 cm of soil depth and analyzed in terms of gravel percentage, texture, saturation moisture, organic matter, pH and electrical conductivity in saturation extract, lime percentage, soluble calcium and magnesium, available phosphorus, Cation Exchange Capacity(CEC) and soluble sodium and potassium. Multivariate techniques including Canonical Correspondence Analysis and Multi-Dimensional Scaling were used to explore the relationships of species with environmental and management variables. Seven plants were identified as indicator species due to being significantly correlated with management(grazing or non-grazing) and edaphic variables such as CEC, soil texture, pH, CaCO3 percentage and physiographic variable including slope, elevation, and convex and concave formations(p < 0.05). Overall, overgrazing and its subsequent effects on soil characteristics, loss of vegetation cover and trampling were found as the major causes of deterioration. Sustainable and integrated management practices such as the implementation of appropriate grazing systems were suggested to enhance soil quality and reduce the accelerated erosion in upper dam zones.展开更多
Ecosystems in high-altitude regions are more sensitive and respond more rapidly than other ecosystems to global climate warming.The Qinghai-Tibet Plateau(QTP)of China is an ecologically fragile zone that is sensitive ...Ecosystems in high-altitude regions are more sensitive and respond more rapidly than other ecosystems to global climate warming.The Qinghai-Tibet Plateau(QTP)of China is an ecologically fragile zone that is sensitive to global climate warming.It is of great importance to study the changes in aboveground biomass and species diversity of alpine meadows on the QTP under predicted future climate warming.In this study,we selected an alpine meadow on the QTP as the study object and used infrared radiators as the warming device for a simulation experiment over eight years(2011-2018).We then analyzed the dynamic changes in aboveground biomass and species diversity of the alpine meadow at different time scales,including an early stage of warming(2011-2013)and a late stage of warming(2016-2018),in order to explore the response of alpine meadows to short-term(three years)and long-term warming(eight years).The results showed that the short-term warming increased air temperature by 0.31℃and decreased relative humidity by 2.54%,resulting in the air being warmer and drier.The long-term warming increased air temperature and relative humidity by 0.19℃and 1.47%,respectively,and the air tended to be warmer and wetter.The short-term warming increased soil temperature by 2.44℃and decreased soil moisture by 12.47%,whereas the long-term warming increased soil temperature by 1.76℃and decreased soil moisture by 9.90%.This caused the shallow soil layer to become warmer and drier under both short-term and long-term warming.Furthermore,the degree of soil drought was alleviated with increased warming duration.Under the long-term warming,the importance value and aboveground biomass of plants in different families changed.The importance values of grasses and sedges decreased by 47.56%and 3.67%,respectively,while the importance value of weeds increased by 1.37%.Aboveground biomass of grasses decreased by 36.55%,while those of sedges and weeds increased by 8.09%and 15.24%,respectively.The increase in temperature had a non-significant effect on species diversity.The species diversity indices increased at the early stage of warming and decreased at the late stage of warming,but none of them reached significant levels(P>0.05).Species diversity had no significant correlation with soil temperature and soil moisture under both short-term and long-term warming.Soil temperature and aboveground biomass were positively correlated in the control plots(P=0.014),but negatively correlated under the long-term warming(P=0.013).Therefore,eight years of warming aggravated drought in the shallow soil layer,which is beneficial for the growth of weeds but not for the growth of grasses.Warming changed the structure of alpine meadow communities and had a certain impact on the community species diversity.Our studies have great significance for the protection and effective utilization of alpine vegetation,as well as for the prevention of grassland degradation or desertification in high-altitude regions.展开更多
Background： Knowledge of the different kinds of tree communities that currently exist can provide a baseline for assessing the ecological attributes of forests and monitoring future changes. Forest inventory data can...Background： Knowledge of the different kinds of tree communities that currently exist can provide a baseline for assessing the ecological attributes of forests and monitoring future changes. Forest inventory data can facilitate the development of this baseline knowledge across broad extents, but they first must be classified into forest community types. Here, we compared three alternative classifications across the United States using data from over 117,000 U.S. Department of Agriculture Forest Service Forest Inventory and Analysis （FIA） plots. Methods： Each plot had three forest community type labels： （1） ＂FIA＂ types were assigned by the FIA program using a supervised method; （2） ＂USNVC＂ types were assigned via a key based on the U.S. National Vegetation Classification; （3） ＂empirical＂ types resulted from unsupervised clustering of tree species information. We assessed the degree to which analog classes occurred among classifications, compared indicator species values, and used random forest models to determine how well the classifications could be predicted using environmental variables. Results： The classifications generated groups of classes that had broadly similar distributions, but often there was no one-to-one analog across the classifications. The Iongleaf pine forest community type stood out as the exception： it was the only class with strong analogs across all classifications. Analogs were most lacking for forest community types with species that occurred across a range of geographic and environmental conditions, such as Ioblolly pine types, indicator species metrics were generally high for the USNVC, suggesting that LJSNVC classes are floristically well-defined. The empirical classification was best predicted by environmental variables. The most important predictors differed slightly but were broadly similar across all classifications, and included slope, amount of forest in the surrounding landscape, average minimum temperature, and other climate variables. Conclusions： The classifications have similarities and differences that reflect their differing approaches and Dbjectives. They are most consistent for forest community types that occur in a relatively narrow range of Invironmental conditions, and differ most for types with wide-ranging tree species. Environmental variables at variety of scales were important for predicting all classifications, though strongest for the empirical and FIA, guggesting that each is useful for studying how forest communities respond to of multi-scale environmental processes, including global change drivers.展开更多
Types and structure of plant communities in the Yellow River Delta were investigated by using detrended canonical correspon-dence analyses(DCCAs) and a two-way indicator species analysis(TWINSPAN).The distribution pat...Types and structure of plant communities in the Yellow River Delta were investigated by using detrended canonical correspon-dence analyses(DCCAs) and a two-way indicator species analysis(TWINSPAN).The distribution pattern and influential factors of the plant communities were also analyzed by testing elevation, slope, soil characteristics, longitude and latitude of 134 vegetation samples collected by representative plot sampling methods.Results showed that all the 134 vegetation samples could be divided into seven vegetation groups, separately dominated by Robinia pseucdoacacia, Imperata cylindrical, Miscanthus saccharifleus, Suaeda salsa, Aeluropus sinensis, Phragmites australis and Tamarix chinensis.The vegetation distribution pattern was mainly related to elevation, ground water depth and soil characteristics such as salinity and soluble potassium.Among the factors affecting distribution pattern of the plant communities, the species matrix explained by non-spatial environmental variation accounts for 45.2% of total variation.Spatial variation and spatial-structured environmental variation explain 11.8%, and 2.2%, respectively.Remained 40.8% of undetermined variation is attributed to biological and stochastic factors.展开更多
基金Isfahan University of Technology for its financial support and laboratory facilities
文摘This study aimed to identify indicator species and explore the most important environmental and management variables contributing to vegetation distribution in a hilly upper dam landscape in Zagros Mountain chain, Iran. A stratified random sampling method was used to collect topographic, edaphic, management and vegetation data. The density and cover percentage of perennial species were measured quantitatively. Indicator species were identified using the two-way indicator species analysis. Besides calculating physiognomic factors in sample sites, 24 soil samples were collected from 0 to 30 cm of soil depth and analyzed in terms of gravel percentage, texture, saturation moisture, organic matter, pH and electrical conductivity in saturation extract, lime percentage, soluble calcium and magnesium, available phosphorus, Cation Exchange Capacity(CEC) and soluble sodium and potassium. Multivariate techniques including Canonical Correspondence Analysis and Multi-Dimensional Scaling were used to explore the relationships of species with environmental and management variables. Seven plants were identified as indicator species due to being significantly correlated with management(grazing or non-grazing) and edaphic variables such as CEC, soil texture, pH, CaCO3 percentage and physiographic variable including slope, elevation, and convex and concave formations(p < 0.05). Overall, overgrazing and its subsequent effects on soil characteristics, loss of vegetation cover and trampling were found as the major causes of deterioration. Sustainable and integrated management practices such as the implementation of appropriate grazing systems were suggested to enhance soil quality and reduce the accelerated erosion in upper dam zones.
基金This study was financially supported by the National Natural Science Foundation of China(41501219)the Applied Basic Research Project of Shanxi Province(2016021136)+2 种基金the National College Students'Innovative Entrepreneurial Training Plan Program of China(201910119007)the Research Project of Philosophy and Social Sciences in Colleges and Universities of Shanxi Province(2019W134)the Soft Science Research Project of Shanxi Province(2018041072-1).
文摘Ecosystems in high-altitude regions are more sensitive and respond more rapidly than other ecosystems to global climate warming.The Qinghai-Tibet Plateau(QTP)of China is an ecologically fragile zone that is sensitive to global climate warming.It is of great importance to study the changes in aboveground biomass and species diversity of alpine meadows on the QTP under predicted future climate warming.In this study,we selected an alpine meadow on the QTP as the study object and used infrared radiators as the warming device for a simulation experiment over eight years(2011-2018).We then analyzed the dynamic changes in aboveground biomass and species diversity of the alpine meadow at different time scales,including an early stage of warming(2011-2013)and a late stage of warming(2016-2018),in order to explore the response of alpine meadows to short-term(three years)and long-term warming(eight years).The results showed that the short-term warming increased air temperature by 0.31℃and decreased relative humidity by 2.54%,resulting in the air being warmer and drier.The long-term warming increased air temperature and relative humidity by 0.19℃and 1.47%,respectively,and the air tended to be warmer and wetter.The short-term warming increased soil temperature by 2.44℃and decreased soil moisture by 12.47%,whereas the long-term warming increased soil temperature by 1.76℃and decreased soil moisture by 9.90%.This caused the shallow soil layer to become warmer and drier under both short-term and long-term warming.Furthermore,the degree of soil drought was alleviated with increased warming duration.Under the long-term warming,the importance value and aboveground biomass of plants in different families changed.The importance values of grasses and sedges decreased by 47.56%and 3.67%,respectively,while the importance value of weeds increased by 1.37%.Aboveground biomass of grasses decreased by 36.55%,while those of sedges and weeds increased by 8.09%and 15.24%,respectively.The increase in temperature had a non-significant effect on species diversity.The species diversity indices increased at the early stage of warming and decreased at the late stage of warming,but none of them reached significant levels(P>0.05).Species diversity had no significant correlation with soil temperature and soil moisture under both short-term and long-term warming.Soil temperature and aboveground biomass were positively correlated in the control plots(P=0.014),but negatively correlated under the long-term warming(P=0.013).Therefore,eight years of warming aggravated drought in the shallow soil layer,which is beneficial for the growth of weeds but not for the growth of grasses.Warming changed the structure of alpine meadow communities and had a certain impact on the community species diversity.Our studies have great significance for the protection and effective utilization of alpine vegetation,as well as for the prevention of grassland degradation or desertification in high-altitude regions.
基金Funding for this work came from the USDA Forest Service Resources Planning Act Assessment,via an agreement with North Carolina State University
文摘Background： Knowledge of the different kinds of tree communities that currently exist can provide a baseline for assessing the ecological attributes of forests and monitoring future changes. Forest inventory data can facilitate the development of this baseline knowledge across broad extents, but they first must be classified into forest community types. Here, we compared three alternative classifications across the United States using data from over 117,000 U.S. Department of Agriculture Forest Service Forest Inventory and Analysis （FIA） plots. Methods： Each plot had three forest community type labels： （1） ＂FIA＂ types were assigned by the FIA program using a supervised method; （2） ＂USNVC＂ types were assigned via a key based on the U.S. National Vegetation Classification; （3） ＂empirical＂ types resulted from unsupervised clustering of tree species information. We assessed the degree to which analog classes occurred among classifications, compared indicator species values, and used random forest models to determine how well the classifications could be predicted using environmental variables. Results： The classifications generated groups of classes that had broadly similar distributions, but often there was no one-to-one analog across the classifications. The Iongleaf pine forest community type stood out as the exception： it was the only class with strong analogs across all classifications. Analogs were most lacking for forest community types with species that occurred across a range of geographic and environmental conditions, such as Ioblolly pine types, indicator species metrics were generally high for the USNVC, suggesting that LJSNVC classes are floristically well-defined. The empirical classification was best predicted by environmental variables. The most important predictors differed slightly but were broadly similar across all classifications, and included slope, amount of forest in the surrounding landscape, average minimum temperature, and other climate variables. Conclusions： The classifications have similarities and differences that reflect their differing approaches and Dbjectives. They are most consistent for forest community types that occur in a relatively narrow range of Invironmental conditions, and differ most for types with wide-ranging tree species. Environmental variables at variety of scales were important for predicting all classifications, though strongest for the empirical and FIA, guggesting that each is useful for studying how forest communities respond to of multi-scale environmental processes, including global change drivers.
基金supported by the Na-tional Natural Science Foundation of China (No. 40771172)the orientation project of the Chinese Academy of Sciences (No. kzcx2-yw-308)
文摘Types and structure of plant communities in the Yellow River Delta were investigated by using detrended canonical correspon-dence analyses(DCCAs) and a two-way indicator species analysis(TWINSPAN).The distribution pattern and influential factors of the plant communities were also analyzed by testing elevation, slope, soil characteristics, longitude and latitude of 134 vegetation samples collected by representative plot sampling methods.Results showed that all the 134 vegetation samples could be divided into seven vegetation groups, separately dominated by Robinia pseucdoacacia, Imperata cylindrical, Miscanthus saccharifleus, Suaeda salsa, Aeluropus sinensis, Phragmites australis and Tamarix chinensis.The vegetation distribution pattern was mainly related to elevation, ground water depth and soil characteristics such as salinity and soluble potassium.Among the factors affecting distribution pattern of the plant communities, the species matrix explained by non-spatial environmental variation accounts for 45.2% of total variation.Spatial variation and spatial-structured environmental variation explain 11.8%, and 2.2%, respectively.Remained 40.8% of undetermined variation is attributed to biological and stochastic factors.
